Update README.md

README.md

@@ -48,9 +48,9 @@ LightGBMLSS currently supports the following [PyTorch distributions](https://pyt
 | [Laplace](https://pytorch.org/docs/stable/distributions.html#laplace)                                                                | `Laplace()`               | Continuous <br /> (Univariate)             | $y \in (-\infty,\infty)$        | 2                               |
 | [LogNormal](https://pytorch.org/docs/stable/distributions.html#lognormal)                                                            | `LogNormal()`             | Continuous <br /> (Univariate)             | $y \in (0,\infty)$              | 2                               |
 | [Negative Binomial](https://pytorch.org/docs/stable/distributions.html#negativebinomial)                                             | `NegativeBinomial()`      | Discrete Count <br /> (Univariate)         | $y \in (0, 1, 2, 3, \ldots)$    | 2                               |
-| [Spline Flow](https://docs.pyro.ai/en/stable/distributions.html#pyro.distributions.transforms.Spline)                                | `SplineFlow()`            | Continuous \& Discrete Count <br /> (Univariate)   | $y \in (-\infty,\infty)$ <br /> <br /> $y \in [0, \infty)$  <br  /> <br /> $y \in [0, 1]$  <br  />  <br /> $y \in (0, 1, 2, 3, \ldots)$ | 2xcount_bins + (count_bins-1) (order=quadratic)  <br  /> <br  />  3xcount_bins + (count_bins-1) (order=linear)                            |
 | [Poisson](https://pytorch.org/docs/stable/distributions.html#poisson)                                                                | `Poisson()`               | Discrete Count <br /> (Univariate)         | $y \in (0, 1, 2, 3, \ldots)$    | 1                               |
 | [Student-T](https://pytorch.org/docs/stable/distributions.html#studentt)                                                             | `StudentT()`              | Continuous <br /> (Univariate)             | $y \in (-\infty,\infty)$        | 3                               |
+| [Spline Flow](https://docs.pyro.ai/en/stable/distributions.html#pyro.distributions.transforms.Spline)                                | `SplineFlow()`            | Continuous \& Discrete Count <br /> (Univariate)   | $y \in (-\infty,\infty)$ <br /> <br /> $y \in [0, \infty)$  <br  /> <br /> $y \in [0, 1]$  <br  />  <br /> $y \in (0, 1, 2, 3, \ldots)$ | 2xcount_bins + (count_bins-1) (order=quadratic)  <br  /> <br  />  3xcount_bins + (count_bins-1) (order=linear)                            |
 | [Weibull](https://pytorch.org/docs/stable/distributions.html#weibull)                                                                | `Weibull()`               | Continuous <br /> (Univariate)             | $y \in [0, \infty)$             | 2                               |
 | [Zero-Adjusted Beta](https://github.com/pyro-ppl/pyro/blob/dev/pyro/distributions/zero_inflated.py)                                  | `ZABeta()`                | Discrete-Continuous <br /> (Univariate)    | $y \in [0, 1)$                  | 3                               |
 | [Zero-Adjusted Gamma](https://github.com/pyro-ppl/pyro/blob/dev/pyro/distributions/zero_inflated.py)                                 | `ZAGamma()`               | Discrete-Continuous <br /> (Univariate)    | $y \in [0, \infty)$             | 3                               |